Traditional methods for the detection of ship and turbulence in water typically required extensive human interaction, including visual inspection of every aerial photograph. Reviewers look for visible objects like ships, wakes left by vehicles moving through the water, and ocean turbulence, among other visible objects. Computers are also used to scan aerial photographs in digital form for the presence of visible objects.
However, there is an upper limit to how many photographs can be reviewed by a single human during any given period of time, and visual inspection by human eyes is not always accurate or consistent. Although computers provide consistency when scanning images for visible objects, these objects are often confused with natural phenomenon such as waves, whiteheads, and other objects. As a result, existing methods for reviewing aerial or satellite imagery of maritime surfaces are both time-consuming and inaccurate.
Accordingly, there is a need for quick and efficient image processing methods, systems, and algorithms to assist with the accurate detection of target features in maritime imagery.